Synthetic humans: ethics, use cases, and guardrails

Imagine a digital agent that doesn’t just talk at you, but sees you, hears you, and responds in real time—mirroring the presence and empathy of a true human conversation.

Synthetic humans, sometimes called AI humans, are not science fiction or static avatars. They are a new class of real-time, lifelike agents designed to bring authentic presence, emotional intelligence, and massive scale to digital experiences. Whether you’re interacting with a concierge kiosk, a virtual tutor, or a digital hiring assistant, these AI humans can interpret your tone, read your body language, and adapt their responses—making every interaction feel alive and personal.

A working definition for teams

At their core, synthetic humans are a leap beyond chatbots or pre-recorded video avatars. They are built to engage in bi-directional, face-to-face conversations, powered by advanced perception and rendering models. Unlike “synthetic personas” or “synthetic users” used for research or testing, these agents are designed for real, customer-facing interactions. They don’t just process text—they see, listen, and respond with nuance, making them ideal for roles where trust, empathy, and adaptability matter.

In this piece, we cover:

• Synthetic humans are real-time, lifelike agents that see, hear, and respond face to face—bringing presence, empathy, and scale to digital experiences.
• This piece clarifies what synthetic humans are (and are not), why presence matters, and how to deploy them responsibly.
• We’ll map high-impact use cases across support, education, hiring, and in-person kiosks—then detail the guardrails that keep experiences safe and on brand.
• You’ll see how Tavus models—Raven-0 for perception, Sparrow-0 for turn-taking, and Phoenix-3 for rendering—enable natural conversations in 30+ languages with sub-second responsiveness.
• We synthesize external ethics research (NN/g, IBM, eWeek, academic reviews) into a pragmatic governance checklist you can apply from day one.

How the human layer works in practice

What sets synthetic humans apart is their ability to deliver presence—something that’s been missing from most digital interactions. Presence isn’t just about looking realistic; it’s about being attentive, emotionally aware, and responsive in the moment. Tavus models like Raven-0 (for perception), Sparrow-0 (for turn-taking), and Phoenix-3 (for full-face rendering) work together to enable seamless, natural conversations in over 30 languages, with sub-second latency.

This means AI humans can interpret micro-expressions, adapt to your conversational rhythm, and deliver pixel-perfect lip sync—moving well beyond the uncanny valley that plagues traditional avatars.

Here’s why this matters in practice:

• Presence matters because it drives engagement, trust, and retention. For example, Final Round AI saw a 50% boost in engagement and 80% higher retention when using Sparrow-0 for natural turn-taking.
• Unlike asynchronous avatar videos or text-only chatbots, synthetic humans are always “in the room”—ready to adapt, empathize, and act in real time.

Where they differ from avatars, chatbots, and “synthetic users”

It’s important to draw clear lines between synthetic humans and other digital agents. While avatars and chatbots can automate some interactions, they lack the bi-directional presence and perceptive capabilities that define true AI humans. For instance, synthetic humans for user research can emulate intricate behaviors, but they are not substitutes for real, emotionally intelligent conversations. Similarly, “synthetic users” are valuable for pretesting flows but should not be mistaken for agents that can build trust or deliver nuanced support—something highlighted by research from NN/g.

Why presence changes outcomes

Presence is more than a technical achievement—it’s a catalyst for better outcomes across industries. When AI humans can see and respond to context, they build rapport, reduce friction, and unlock new possibilities for support, learning, and engagement. As leaders at Dreamforce put it, synthetic humans represent a “new species” of agentic capability—powerful, but requiring strong ethics and thoughtful deployment. To learn more about how Tavus is shaping this future, visit the Tavus Homepage for an overview of our mission and technology.

Defining synthetic humans: beyond avatars and bots

A working definition for teams

Synthetic humans are not just another step in digital automation—they represent a cognitive leap in how we interact with technology. Unlike scripted videos or text-based chatbots, synthetic humans are real-time, lifelike agents that engage face to face. They see, hear, and respond with attentive, adaptable, and human-feeling conversation, creating a sense of presence and empathy that static interfaces simply can’t match.

At the core of this experience are foundational models like Phoenix-3, which renders full-face micro-expressions with identity preservation and pixel-perfect lip sync, and Sparrow-0, which enables sub-600 ms turn-taking for fluid, natural dialogue. Raven-0 brings perception to the table, interpreting emotion, intent, and context—making every interaction feel alive and responsive. Conversations can run in over 30 languages, ensuring accessibility and inclusivity at scale.

Where they differ from avatars, chatbots, and “synthetic users”

Key differences to keep in mind:

• Synthetic humans: Live, perceptive, and bi-directional—capable of real-time, face-to-face interaction that adapts to user cues and context.
• Avatar videos: Asynchronous and pre-recorded—lacking real-time adaptability or presence.
• Chatbots: Text-only, with no visual or emotional presence—limited to transactional exchanges.
• “Synthetic users”: AI personas used for internal research and testing, not for customer-facing engagement.

This distinction is critical: while avatars and chatbots automate tasks, synthetic humans deliver the warmth, nuance, and trust of a real conversation. As explored in this educational overview of conversational video AI, the leap from static avatars to interactive AI humans is as significant as the shift from email to video calls.

Why presence changes outcomes

The impact of presence is measurable. Final Round AI reports a 50% boost in user engagement, 80% higher retention, and twice the response speed when powered by Sparrow-0’s natural turn-taking. Phoenix-3’s full-face animation moves beyond the uncanny valley, making digital interactions feel genuinely human. Meanwhile, knowledge retrieval can return answers in as little as 30 ms, ensuring conversations are both instant and grounded in accurate information.

Examples include:

• ACTO Health leverages Raven-0’s perception to adapt in telehealth, reading patient cues and context for more personalized care.
• At Dreamforce, industry leaders described synthetic humans as a “new species” of agentic capability—powerful, but requiring strong ethical guardrails.

For a deeper dive into how synthetic humans are revolutionizing user research and digital engagement, see AI Synthetic Humans: Revolutionizing User Research & Team Collaboration. And to explore the technical underpinnings and practical applications, visit the Conversational AI Video API documentation.

Where synthetic humans drive value today

Customer and citizen experience

Synthetic humans are redefining what it means to deliver high-touch, humanlike service at scale. In hospitality, government, and retail, AI-powered concierges and kiosk help desks are now available 24/7, offering support that feels attentive and personal. Unlike traditional chatbots, these agents leverage perception models like Raven‑0 to interpret nonverbal cues—such as frustration or confusion—and adapt their responses in real time. This means a guest at a hotel kiosk or a citizen navigating a government portal receives not just answers, but empathy and context-aware guidance.

Meanwhile, Sparrow‑0 ensures conversations flow naturally, eliminating awkward pauses and making interactions feel remarkably lifelike.

Representative use cases include:

• Telehealth intake assistants that streamline patient onboarding and triage, improving both efficiency and patient satisfaction.
• Retail and live shopping advisors who provide real-time, personalized product recommendations and support, bridging the gap between online and in-store experiences.
• Enterprise support kiosks for public spaces, offering multilingual, always-on help that adapts to user needs.
• SDR “first touch” outreach agents that initiate sales conversations with a human touch, increasing engagement rates.
• Compliance and safety training modules that use digital twins to make learning more engaging and memorable.
• Fan and celebrity digital twins for entertainment and brand engagement, enabling interactive experiences at scale.
• Apartment tours and high-consideration purchases, where synthetic humans guide prospects through complex decisions with patience and expertise.

These use cases are not hypothetical—they’re already being deployed by forward-thinking organizations. For example, Tavus’s customer service personas are designed to adapt to user emotions and context, delivering support that feels genuinely human.

Learning, coaching, and hiring

In education and talent development, synthetic humans are transforming how people learn and grow. Lifelike mock interviews, onboarding coaches, and immersive L&D roleplays hold attention far longer than static LMS content. Recruiters can now scale first-round candidate screens with consistent, bias-aware flows, ensuring every applicant receives a fair and engaging experience. ACTO, for instance, replaced unpopular role-play exercises with on-demand, realistic practice sessions powered by Tavus AI Humans—improving both learning outcomes and user satisfaction.

Sales and marketing personalization

Synthetic humans are also unlocking new frontiers in sales and marketing. Brands can deploy personalized product walkthroughs and landing pages using either stock or custom Replicas, generating videos in over 30 languages.

By combining Retrieval-Augmented Generation (RAG) with these lifelike agents, companies can deliver fast, grounded answers—often in as little as 30 milliseconds—creating seamless, interactive buyer journeys. This approach not only boosts conversion rates but also differentiates brands in crowded markets. For a deeper dive into how digital twins are reshaping online engagement, see Synthetic Humans: Digital Twins Living and Breathing Online.

Research and testing with synthetic users (use with care)

While synthetic humans can pretest flows or hypotheses in user research, it’s important to recognize their limitations. As highlighted by NN/g, “synthetic users” are valuable for early-stage feedback but cannot replace real users when validating usability, accessibility, or market fit. Always triangulate findings with real user evidence to ensure your solutions truly resonate. For more on this evolving research practice, explore AI Synthetic Humans: Revolutionizing User Research.

Building responsibly: ethics, governance, and guardrails

Consent, identity, and transparency

Building synthetic humans is a cognitive leap—one that brings both opportunity and responsibility. As these lifelike agents become more present in our daily workflows, ethical stewardship is non-negotiable. Responsible deployment starts with explicit consent, especially when creating personal Replicas. For example, Phoenix‑3 can train a personal Replica from just two minutes of video, but this process always requires a verbal consent video to safeguard identity and agency. Transparency is equally critical: users must know when they’re interacting with an AI, what data is being used, and how their information is handled.

Core transparency and consent requirements include:

• Require explicit consent for personal Replicas (verbal consent video is mandatory)
• Clearly disclose when an agent is AI—not a human
• Publish session recording policies and provide opt-outs
• Offer clear escalation paths to a human when needed
• Maintain audit logs and trigger callback alerts on policy violations

Consistent disclosure is a cornerstone of trust. Teams should always communicate who built the AI, what knowledge sources ground its responses (such as knowledge base documents), when memory is active, when conversations are recorded, what information is stored, and how users can reach a human for support. For a deeper dive into these practices, the Berkman Klein Center’s research on AI ethics and governance offers a comprehensive perspective.

Safety by design with objectives and guardrails

Ethical AI isn’t just about policies—it’s about real-time enforcement. Tavus enables teams to define Objectives and Guardrails that operate at runtime, ensuring every interaction stays on brand and within safe boundaries. Guardrails are structured as JSON objects, specifying the name, prompt, modality (verbal or visual), and optional callback URLs for alerts. This approach allows you to restrict sensitive topics, enforce compliance, and receive instant notifications if a guardrail is triggered. The Persona Builder makes it easy to test edge cases and iterate quickly, so your synthetic human adapts to real-world scenarios without compromising safety.

To operationalize safety, teams should:

• Define clear goals, restricted topics, and modalities for each persona
• Use callbacks to alert teams when guardrails are activated
• Test edge cases and continuously improve guardrails in the Persona Builder
• Disclose consistently: who built the AI, what data grounds responses, when memory is used, when conversations are recorded, what gets stored, and how to reach a human

Following cross-industry guidance—such as best practices for AI ethics in research and IBM’s data minimization standards—means prioritizing role-based access, bias evaluation, and ongoing red-team testing. For organizations with advanced compliance needs, Tavus enterprise plans offer SOC 2 and HIPAA options, ensuring robust governance from day one. To learn more about how Tavus implements these safeguards, visit the Guardrails documentation.

Move from pilot to production—safely and fast

Start with one high‑value interaction

The fastest path to value with synthetic humans is to focus on a single, high-leverage moment—think health intake, recruiter screen, or a concierge kiosk. By narrowing your scope, you can define clear Objectives for your AI Persona, bind Guardrails that ensure safety and compliance, and test with real users in a controlled environment. This approach not only accelerates learning but also builds trust and confidence before you scale.

A 30‑day plan for responsible rollout:

• Week 1: Choose your use case and set success metrics (NPS, retention, CSAT).
• Week 2: Configure your Persona, Objectives, and Guardrails using the Persona Builder.
• Week 3: Red-team your setup and run a monitored beta with real users.
• Week 4: Instrument alerts, publish disclosures, and go live with a human‑in‑the‑loop for oversight.

Apply guardrails before you scale

Guardrails are your safety net—strict behavioral boundaries that keep your AI Persona on brand and compliant. With Tavus, you can define Guardrails at the Persona level, specifying exactly which topics, behaviors, or responses are restricted. For example, a healthcare intake assistant might be bound by Guardrails that prevent sharing sensitive medical information or providing advice outside approved guidelines. These can be configured visually or via API, and are rigorously enforced in every conversation. For more on how to create and manage Guardrails, see the Tavus documentation on Guardrails.

Practical ramp to production:

• Prototype with stock Replicas to validate flows and user experience.
• Train a Personal Replica with as little as two minutes of video—training typically takes four to six hours.
• Localize your Persona to 30+ languages for global reach.

Be transparent to earn trust

Transparency is essential for building user trust as you move from pilot to production. Always disclose when memory is active, what data grounds your AI’s responses, and when conversations are being recorded. Tavus enables ultra-fast, grounded responses by attaching your Knowledge Base for retrieval in as little as 30 milliseconds—ensuring answers are accurate and up to date. This level of speed and clarity is a key differentiator, as highlighted in AI Synthetic Humans: Revolutionizing User Research, which underscores the importance of real-time, reliable feedback in digital experiences.

Get hands‑on with Tavus

Ready to try it yourself? The free plan includes 25 minutes of Conversational Video and 5 minutes of Video Generation, making it easy to experiment and iterate before committing to a larger rollout. The Persona Builder guides you through generating objectives and guardrails, so you can ship human‑first AI with confidence. For a deeper dive into how Tavus is shaping the future of conversational video AI, visit the Tavus Homepage.

As synthetic humans move from pilot to production, the key is to combine speed with safety—delivering presence and empathy at scale, while keeping every interaction grounded, transparent, and aligned with your brand’s values. For a broader perspective on the future landscape, see why synthetic sentiences are projected to vastly outnumber humans by 2035.

If you’re ready to build your first synthetic human, get started with Tavus today—we hope this post was helpful.